class_docstr: Smallnorb data set.
docstr: Generate examples for the Smallnorb dataset.
  
  Args:
    split_prefix: Prefix that identifies the split.
    dat_path: Path to dat file of the chunk.
    cat_path: Path to cat file of the chunk.
    info_path: Path to info file of the chunk.
  
  Yields:
    Dictionaries with images and the different labels.
docstr_tok: ["Generate","examples","for","the","Smallnorb","dataset",".","Args",":","split_prefix",":","Prefix","that","identifies","the","split",".","dat_path",":","Path","to","dat","file","of","the","chunk",".","cat_path",":","Path","to","cat","file","of","the","chunk",".","info_path",":","Path","to","info","file","of","the","chunk",".","Yields",":","Dictionaries","with","images","and","the","different","labels","."]
code: def _generate_examples(
      self, split_prefix, dat_path, cat_path, info_path
  ):
      """Generate examples for the Smallnorb dataset.
  
      Args:
        split_prefix: Prefix that identifies the split.
        dat_path: Path to dat file of the chunk.
        cat_path: Path to cat file of the chunk.
        info_path: Path to info file of the chunk.
  
      Yields:
        Dictionaries with images and the different labels.
      """
      dat_arr, cat_arr, info_arr = _load_chunk(
          dat_path, cat_path, info_path
      )
  
      for i, (image, category, info_vec) in enumerate(
          zip(dat_arr, cat_arr, info_arr)
      ):
          record = {
              "image": image[0],
              "image2": image[1],
              "label_category": category,
              "instance": info_vec[0],
              "label_elevation": info_vec[1],
              "label_azimuth": info_vec[2],
              "label_lighting": info_vec[3],
          }
          if self.version > "2.0.0":
              record["id"] = "{}{:05d}".format(split_prefix, i)
          yield i, record
  
file_path: datasets/tensorflow_datasets/datasets/smallnorb/smallnorb_dataset_builder.py
imports: import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the Builder obj's underlying member method code with example usage: obj._generate_examples(split_prefix, dat_path, cat_path, info_path) without return types